Climatic factors such as temperature, rainfall, snowfall, cloudiness and winds have a significant impact on many aspects of the nation's economy as well as on human health and quality of life. The Department of Commerce Bureau of Economic Analysis estimates that 42% of the U.S. Gross National Product is climate sensitive. Weather is frequently used to explain seasonal and year-to-year changes in economic performance, but the explanations are often subjective and many times based on perceptions rather than clear observational evidence.

The National Oceanic and Atmospheric Administration's (NOAA) National Climatic Data Center (NCDC) has developed climate indices to provide public and private sector analysts with up-to-date quantitative information relating the effects of weather and climate to vital sectors of the U.S. economy and society. Although index development is ongoing, two indices currently provide valuable information related to crop yield and energy usage in the U.S. The crop Moisture Stress Index (MSI) reflects the influence of severe drought and catastrophic wetness on annual crop yield for corn and soybean crops, and the Residential Energy Demand Temperature Index (REDTI) provides quantitative information on the impact of seasonal temperatures on residential energy demand.

This paper will review the methodology used to compute the MSI and REDTI indices and discuss their utility in operational climate monitoring and in putting current anomalies into a century-scale historical perspective.